Tax planning using video-based graphical user interface and artificial intelligence

ABSTRACT

A system and method of generating and presenting a recommended filing strategy that includes receiving user inputs via a graphical user interface; identifying, using one or more computers, factual patterns of the user inputs; assigning, using the one or more computers and based on the identified factual patterns, a risk tolerance classification; generating, using an optimization model and based on the factual patterns, the risk tolerance classification, and relevant legal documents, the recommended filing strategy; identifying relevant media files from a library of media files that are associated with the recommended filing strategy; creating a combined media file from the plurality of relevant media files; and presenting the combined media file via the graphical user interface.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/354,554, filed Jun. 22, 2021, which claims the benefit of the filingdate of, and priority to, U.S. Application No. 63/049,465, filed Jul. 8,2020, the entire disclosures of which are hereby incorporated herein byreference.

BACKGROUND

This disclosure relates to tax planning using a video-based graphicaluser interface and artificial intelligence.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic illustration of a system according to anexample embodiment, the system including a remote user device, theremote user device including a graphical user interface.

FIG. 2 is a flow chart illustration of a method of operating the systemof FIG. 1, according to an example embodiment.

FIG. 3 is a data flow diagram associated with the system of FIG. 1,according to an example embodiment.

FIG. 4 is listing of user-provided data used by the system of FIG. 1,according to an example embodiment.

FIG. 5 is listing of historical data used by the system of FIG. 1,according to an example embodiment.

FIG. 6 is a diagrammatic illustration of the remote user device of FIG.1, according to an example embodiment.

FIG. 7 is a diagrammatic illustration of a node for implementing one ormore example embodiments of the present disclosure, according to anexample embodiment.

DETAILED DESCRIPTION

In an example embodiment, as illustrated in one or more of the FIGS.1-7, a tax planning system that includes a video-based graphical userinterface results in customized compilation video that, in someembodiments, relates to creative legal positions. The system can be usedto present, via the graphical user interface, a tax opinion or advicethat is customized to the user. This opinion or advice is “on demand” tothe user in some embodiments.

In some embodiments, the system includes a “confidence threshold”associated with the tax opinion or advice. In some examples, the“confidence threshold” is based on existing case law and/or otherjudiciary data. For example, case law stemming from different courts maybe weighted differently based on the judge(s) that issued the opinionand/or the court that issued the opinion. For example, a holding fromthe Second Circuit Court of Appeals may be weighted heavier than aholding from the Ninth Circuit Court of Appeals. Moreover, whether theopinion was unanimous, or a split decision is also considered, as wellas which judges sided with the majority or dissent. In some cases,appointment details relating to each judge is considered as well.

In an example embodiment, referring to FIG. 1, a system 10 includes aremote user device 15 that includes a graphical user interface 15 a, aserver 20, a computer 25, and artificial intelligence (“AI”) 27connected via a network 30. Generally, the computer 25 includes acomputer processor 35 and a non-transitory computer readable medium 40operably coupled thereto. Instructions accessible to, and executable by,the computer processor 35 are stored on the computer readable medium 40.A database 45 is also stored in the computer readable medium 40. In someembodiments, the user provides inputs to the system 10 via a window thatis displayed on the GUI 15 a but may provide inputs using differentinput mechanisms. In some embodiments, a video from a video librarystored in the server 20 is displayed on the GUI 15 a. In otherembodiments, a compilation video that is formed from one or more videosin the video library is displayed on the GUI 15 a. In some embodiments,the server 20 is part of the computer 25. In some embodiments, thecomputer 25 is part of the server 20.

In an example embodiment, as illustrated in FIG. 2 with continuingreference to FIG. 1, a method 200 includes receiving inputs at step 205;identifying factual patterns in the inputs at step 210; generating a taxsolution at step 215; identifying relevant videos based on the taxsolution at step 220; compiling relevant videos at step 225; displayingthe tax solution and compilation video at step 230; and generating taxdocuments based on the tax solution and/or the inputs at step 235.

In some embodiments and at step 205, the inputs are received. FIG. 3illustrates one embodiment of a data flow associated with the system 10.Generally, at least a portion of the inputs are received via the GUI,but could also be received via a microphone, keyboard, or other inputmechanism. In some embodiments, the inputs may include user provideddata, a tax schedule, rules, historical data, and decisions variables.

In some embodiments and as illustrated in FIG. 4, the user provided datamay include user tax data and other user data. User tax data may includedata that is relevant to the user's potential tax liability, whichincludes data relating to a potential tax deduction, expenses, losses,investments, depreciation, indebtedness, potential tax credit,expenditures, gains, carryovers, charitable contributions, etc. In someembodiments, other user data may be related to a psychological profileof the user and/or related to data useful in a risk tolerance evaluationof the user. In some embodiments, the system 10 accessing data is thesame as the system 10 receiving data in the step 205. That is, the step205 includes the system 10 accessing data related to the user fromanother system. For example, the user may provide permission to thesystem 10 to access his or her data (i.e., user tax data or other userdata) by allowing the system 10 to access his or her most recent orhistorical Form W-2, Schedule K-1, etc.

In some embodiments and as illustrated in FIG. 5, historical data mayinclude historical judiciary data, historical litigation data, and/orhistorical audit data. The historical judiciary data may include datarelating to judges themselves (e.g., appointment data, decision data,etc.), as well as data relating to specific case law (e.g., court fromwhich case law was issued, compilation of judges for panel review,specific facts relating to opinions, etc.). In some embodiments, thehistorical audit data includes data relating to audits or other reviewsperformed by an administrative or other governmental body.

Referring back to FIGS. 2 and 3, at the step 210, factual patterns areidentified by the system 10. Generally, the system 10 analyzes dataprovided by the client/user and applies said user-provided data to apreviously unknown and novel formulaic technique involving sets ofpre-programmed mathematical models, collections of algorithms, and setsof rules to both accurately identify and score the strengths ofapplicable legal authorities, the ideological inclinations of federaljudges, and the ideology of the executive branch when any administrativerulings were issued with self-adjustments for evolutionary computation.In some embodiments, the step 210 includes an optimization module thatincludes the sets of pre-programmed mathematical models and collectionsof algorithms. In some embodiments, the optimization module referencesthe rules or otherwise includes the rules. Regardless, the inputs areused by the optimization module and the rules to identify factualpatterns.

In some embodiments and at the step 215, the system 10 generates a taxsolution. Using the identified factual patterns, the system 10 generatesa tax solution. In some embodiments, the tax solution depends on theuser's risk tolerance. The tax solution may include proposed actions tobe taken in the future to adjust one's tax liability and/or may includeclassifying past actions/expenses differently to affect one's taxliability. In some embodiments, the tax solution may include adopting orrelying on a legal position relating to one's tax liability orclassification. In some embodiments, the system 10 identifies orassociates key identifiers with the tax solution. For example, the taxsolution may be associated with a key identifier of “exit tax planning”or “offshore tax compliance.”

In some embodiments and at step 220, the system 10 identifies relevantvideos based on the tax solution. In some embodiments and using the keyidentifier(s) associated with the tax solution, the system 10 identifiesvideos within the video library that are relevant to the tax solution.In some embodiments, the identification of the relevant videos is alsodependent upon the user's risk tolerance so that the identification ofthe relevant videos is based on a combination of the key identifier andthe user's risk tolerance. The video library may include videos thatdescribe a subject in a manner that is dependent upon the user's risktolerance. For example, and when the user has a low risk tolerance andthe key identifier is “exit tax planning”, a first video may highlightthe conservative aspects relating to “exit tax planning”. Meanwhile,when the user has a high risk tolerance, a second video may omit theconservative aspects relating to the “exit tax planning.”

In some embodiments and at step 225, the system 10 compiles the relevantvideos. In some embodiments, the system 10 provides a single video thatincludes the identified relevant videos. In some embodiments, the system10 configures the single video such that the transitions betweenidentified videos is smooth and/or not noticeable. Regardless, thecompilation video is customized to the user and his or her tax situationand risk tolerance.

In some embodiments and at step 230, the system 10 displays the taxsolution and the compilation video. Generally, the tax solution and thecompilation video are displayed via the GUI. In some embodiments, thetax solution is the compilation video but in other embodiments the taxsolution is a separate file, which may be a word file, a PDF file, orany other type of file that is not limited to a video file. In someembodiments, the compilation video file is a multi-media file. In someembodiments, the system 10 automatically stores the compilation videoand associates the compilation video with the user.

In some embodiments and at step 235, the system 10 generates taxdocuments based on the tax solution and/or the inputs. In someembodiments, the system 10 prepopulates templates using the tax solutionand/or the inputs. However, in other embodiments, the system 10generates a tax opinion based on the tax solution and/or the inputs.

In some embodiments, the AI 27 is a software, service, or platform. Insome embodiments, the AI 27 is or includes a machine learning platform.In some embodiments, the AI 27 is or includes IBM Watson, RapidMiner,MATLAB, Tableau Server, RStudio, Azure Machine Learning Studio, orsimilar.

In some embodiments, the method 200 includes using the AI 27 to interactwith the user, to receive the inputs, to generate the tax solution, tocompile the relevant videos, or any combination thereof. In someembodiments, the AI 27 may be used in one or more of the steps of themethod 200.

In an example embodiment, as illustrated in FIG. 6 with continuingreference to FIG. 1, the remote user device 15 includes the GUI 15 a, acomputer processor 15 b and a computer readable medium 15 c operablycoupled thereto. Instructions accessible to, and executable by, thecomputer processor 15 b are stored on the computer readable medium 15 c.A database 15 d is also stored in the computer readable medium 15 c.Generally, the GUI 15 a is capable of display a plurality of windows orscreens to the user. The computer 15 also includes an input device 15 eand an output device 15 f. In some embodiments, the input device 15 eand the output device 15 f are the GUI 15 a.

In some embodiments, the system 10 includes an application or software“AiTax” that has the ability to, based on basic data provided by theclient/user, identify factual patterns in user-provided data (839 F.3d1089) to generate user-specific tax planning solutions (778 Fed.Appx.935) as well as definitively state whether a taxpayer's legal positionon a federal income tax return will result in an IRS audit, besufficient to avoid penalties, and, if litigated, accurately predict theoutcome of a tax court case in any jurisdiction by again analyzing dataprovided by the client and applying said user-provided data to apreviously unknown and novel formulaic technique involving sets ofpre-programmed mathematical models, collections of algorithms, and setsof rules to both accurately identify and score the strengths ofapplicable legal authorities, the ideological inclinations of federaljudges, and the ideology of the executive branch when any administrativerulings were issued with self-adjustments for evolutionary computationcombined with an entirely novel, video-based graphical user interfacethat produces a user experience akin to human interaction with ahighly-skilled tax professional. (880 F.3d 1356). The manner by whichthe videos are presented to the user will be based on a system forfiltering and presenting only relevant video content from a vast libraryof explanatory videos. (827 F.3d 1341).

The software/application will also create a single record foraccounting, tax planning, and estate planning purposes (841 F.3d 1288)that will be utilized to make complex tax forms, financials, and estateplanning documents more simple and easy to generate without the need ofhaving to re-enter any user information. (906 F.3d 999).

The ability to definitively predict whether a taxpayer's legal positionon a federal income tax return will result in an IRS audit, besufficient to avoid penalties, and, if litigated, accurately predict theoutcome of a tax court case in any jurisdiction by analyzing dataprovided by client and applying it to a previously unknown formulaictechnique involving sets of pre-programmed mathematical models,collections of algorithms, and sets of rules to both accurately identifyand score the strengths of applicable legal authorities and theideological inclinations of federal judges combined withself-adjustments for evolutionary computation.

In some embodiments, an ideological score is assigned to every federaljudge in the U.S. and then the system 10 uses that score to (1) eithergive deference to taxpayers or the IRS and (2) either give more weightto established case law or consider judicial trends and social impact.Conventional systems have never assigned this score. Scores are alsoassigned to various legal authorities: case law, statutory language,regulatory interpretation, revenue rulings, revenue procedures, privateletter rulings, etc. In some embodiments, the system 10 assigns thescore(s) but in other embodiments an administrator of the system 10assigns the score(s). The legal authorities score is somewhat objective,but, the addition of the ideological score considers an interpretationof the authority to account for the legal authority being interpreted inthe “eye of the beholder.” As such, the interpretation or predictedinterpretation is changed when the judicial formula/scoring is applied.The predicted interpretation may indicate interpretation of theauthorities in favor of either the taxpayer or the IRS and also predictwhether the interpretation would be based more on established case lawversus emerging trends. One advantage is that the formula is not static;it's dynamic and ever-changing since new judges are always coming in asolder ones retire. In some embodiments, the scores are referenced/usedwhen generating the tax solution. Specifically, in some embodiments thescores are referenced/used when the tax solution includes a predictionor opinion regarding whether portions of the tax solution would besufficient to avoid penalties, and, if litigated, predict the outcome ofa tax court case in any jurisdiction.

In some embodiments, the application is stored in the computer readablemedium. In some embodiments, the application includes and/or executesone or more web-based programs, Intranet-based programs, and/or anycombination thereof. In an example embodiment, the application includesa computer program including a plurality of instructions, data, and/orany combination thereof. In an example embodiment, the application iswritten in, for example, HyperText Markup Language (HTML), CascadingStyle Sheets (CSS), JavaScript, Extensible Markup Language (XML),asynchronous JavaScript and XML (Ajax), and/or any combination thereof.In an example embodiment, the application is a web-based applicationwritten in, for example, Java or Adobe Flex, which pulls real-timeinformation from another computer and/or a plurality of data sources. Inan example embodiment, the application pulls real-time information fromthe plurality of data sources, upon the execution, opening or start-upof the application. In an example embodiment, the application is storedon the computer readable medium and/or in the database.

In an example embodiment, the network 30 includes the Internet, one ormore local area networks, one or more wide area networks, one or morecellular networks, one or more wireless networks, one or more voicenetworks, one or more data networks, one or more communication systems,and/or any combination thereof.

In an example embodiment, as illustrated in FIG. 7 with continuingreference to FIGS. 1-6, an illustrative node 1000 for implementing oneor more of the example embodiments described above and/or illustrated inFIGS. 1-6, is depicted. The node 1000 includes a microprocessor 1000 a,an input device 1000 b, a storage device 1000 c, a video controller 1000d, a system memory 1000 e, a display 1000 f, and a communication device1000 g all interconnected by one or more buses 1000 h. In severalexample embodiments, the storage device 1000 c may include a floppydrive, hard drive, CD-ROM, optical drive, any other form of storagedevice and/or any combination thereof. In several example embodiments,the storage device 1000 c may include, and/or be capable of receiving, afloppy disk, CD-ROM, DVD-ROM, or any other form of computer-readablemedium that may contain executable instructions. In several exampleembodiments, the communication device 1000 g may include a modem,network card, or any other device to enable the node to communicate withother nodes. In several example embodiments, any node represents aplurality of interconnected (whether by intranet or Internet) computersystems, including without limitation, personal computers, mainframes,PDAs, smartphones, and cell phones.

In several example embodiments, one or more of the components of thesystems described above and/or illustrated in FIGS. 1-6, include atleast the node 1000 and/or components thereof, and/or one or more nodesthat are substantially similar to the node 1000 and/or componentsthereof. In several example embodiments, one or more of theabove-described components of the node 1000, the system 10, and/or theexample embodiments described above and/or illustrated in FIGS. 1-6,include respective pluralities of same components.

In several example embodiments, one or more of the applications,systems, and application programs described above and/or illustrated inFIGS. 1-6, include a computer program that includes a plurality ofinstructions, data, and/or any combination thereof; an applicationwritten in, for example, Arena, Hypertext Markup Language (HTML),Cascading Style Sheets (CSS), JavaScript, Extensible Markup Language(XML), asynchronous JavaScript and XML (Ajax), and/or any combinationthereof; a web-based application written in, for example, Java or AdobeFlex, which in several example embodiments pulls real-time informationfrom one or more servers, automatically refreshing with latestinformation at a predetermined time increment; or any combinationthereof.

In several example embodiments, a computer system typically includes atleast hardware capable of executing machine readable instructions, aswell as the software for executing acts (typically machine-readableinstructions) that produce a desired result. In several exampleembodiments, a computer system may include hybrids of hardware andsoftware, as well as computer sub-systems.

In several example embodiments, hardware generally includes at leastprocessor-capable platforms, such as client-machines (also known aspersonal computers or servers), and hand-held processing devices (suchas smart phones, tablet computers, personal digital assistants (PDAs),or personal computing devices (PCDs), for example). In several exampleembodiments, hardware may include any physical device that is capable ofstoring machine-readable instructions, such as memory or other datastorage devices. In several example embodiments, other forms of hardwareinclude hardware sub-systems, including transfer devices such as modems,modem cards, ports, and port cards, for example.

In several example embodiments, software includes any machine codestored in any memory medium, such as RAM or ROM, and machine code storedon other devices (such as floppy disks, flash memory, or a CD ROM, forexample). In several example embodiments, software may include source orobject code. In several example embodiments, software encompasses anyset of instructions capable of being executed on a node such as, forexample, on a client machine or server.

In several example embodiments, combinations of software and hardwarecould also be used for providing enhanced functionality and performancefor certain embodiments of the present disclosure. In an exampleembodiment, software functions may be directly manufactured into asilicon chip. Accordingly, it should be understood that combinations ofhardware and software are also included within the definition of acomputer system and are thus envisioned by the present disclosure aspossible equivalent structures and equivalent methods.

In several example embodiments, computer readable mediums include, forexample, passive data storage, such as a random-access memory (RAM) aswell as semi-permanent data storage such as a compact disk read onlymemory (CD-ROM). One or more example embodiments of the presentdisclosure may be embodied in the RAM of a computer to transform astandard computer into a new specific computing machine. In severalexample embodiments, data structures are defined organizations of datathat may enable an embodiment of the present disclosure. In an exampleembodiment, a data structure may provide an organization of data, or anorganization of executable code.

In several example embodiments, any networks and/or one or more portionsthereof may be designed to work on any specific architecture. In anexample embodiment, one or more portions of any networks may be executedon a single computer, local area networks, client-server networks, widearea networks, internets, hand-held and other portable and wirelessdevices, and networks.

In several example embodiments, a database may be any standard orproprietary database software. In several example embodiments, thedatabase may have fields, records, data, and other database elementsthat may be associated through database specific software. In severalexample embodiments, data may be mapped. In several example embodiments,mapping is the process of associating one data entry with another dataentry. In an example embodiment, the data contained in the location of acharacter file can be mapped to a field in a second table. In severalexample embodiments, the physical location of the database is notlimiting, and the database may be distributed. In an example embodiment,the database may exist remotely from the server, and run on a separateplatform. In an example embodiment, the database may be accessibleacross the Internet. In several example embodiments, more than onedatabase may be implemented.

In several example embodiments, a plurality of instructions stored on anon-transitory computer readable medium may be executed by one or moreprocessors to cause the one or more processors to carry out or implementin whole or in part the above-described operation of each of theabove-described example embodiments of the system, the method, and/orany combination thereof. In several example embodiments, such aprocessor may include one or more of the microprocessor 1000 a, anyprocessor(s) that are part of the components of the system, and/or anycombination thereof, and such a computer readable medium may bedistributed among one or more components of the system. In severalexample embodiments, such a processor may execute the plurality ofinstructions in connection with a virtual computer system. In severalexample embodiments, such a plurality of instructions may communicatedirectly with the one or more processors, and/or may interact with oneor more operating systems, middleware, firmware, other applications,and/or any combination thereof, to cause the one or more processors toexecute the instructions.

The present disclosure introduces a method of generating and presentinga recommended filing strategy, the method including: receiving userinputs via a graphical user interface; identifying, using one or morecomputers, factual patterns of the user inputs; assigning, using the oneor more computers and based on the identified factual patterns, a risktolerance classification; generating, using an optimization model andbased on the factual patterns, the risk tolerance classification, andrelevant legal documents, the recommended filing strategy; identifyingrelevant media files from a library of media files that are associatedwith the recommended filing strategy; creating a combined media filefrom the plurality of relevant media files; and presenting the combinedmedia file via the graphical user interface. In one embodiment, therelevant legal documents are a subset of a plurality of legal documents;wherein the optimization model assigns a strength score to each legaldocument of the plurality of legal documents; and wherein the methodfurther comprises the optimization model identifying the relevant legaldocuments based on the factual patterns In one embodiment, each legaldocument of the plurality of legal documents is associated with one ormore judges from a plurality of federal judges; wherein the methodfurther comprises the optimization model assigning an ideological scoreeach judge of the plurality of federal judges; and wherein theoptimization model generates the recommended filing strategy using theideological score of the judges associated with the relevant legaldocuments. In one embodiment, the method also includes the optimizationmodel predicting an interpretation of the recommended filing strategy byeach judge of the plurality of judges In one embodiment, theinterpretation of the recommended filing strategy by each judge of theplurality of judges comprises a first interpretation in favor of agovernment entity or a second interpretation in favor of anon-government entity In one embodiment, the interpretation of therecommended filing strategy by each judge of the plurality of judges isbased on either the strength score of the relevant legal documents or ajudicial trend. In one embodiment, the user inputs are associated with auser; and wherein the risk tolerance classification indicates whetherthe user has a high level of risk tolerance or a low level of risktolerance. In one embodiment, the combined media file is customized tothe user and the risk tolerance of the user. In one embodiment,presenting, via the graphical user interface, the combined media filecomprises explaining the recommended filing strategy to a user of thegraphical user interface. In one embodiment, the method also includesprepopulating templates using the recommended filing strategy and theuser inputs.

The present disclosure introduces an apparatus configured to generateand present a recommended filing strategy, the apparatus including: anon-transitory computer readable medium having stored thereon aplurality of instructions, wherein the instructions are executed with atleast one processor so that the following steps are executed:identifying factual patterns of the user inputs; assigning, based on theidentified factual patterns, a risk tolerance classification;generating, using an optimization model and based on the factualpatterns, the risk tolerance classification, and relevant legaldocuments, the recommended filing strategy; identifying relevant mediafiles from a library of media files that are associated with therecommended filing strategy; creating a combined media file from theplurality of relevant media files; and presenting the combined mediafile via the graphical user interface. In one embodiment, the relevantlegal documents are a subset of a plurality of legal documents; whereinthe optimization model assigns a strength score to each legal documentof the plurality of legal documents; and wherein, when the instructionsare executed with at least one processor, the following step is alsoexecuted: the optimization model identifies the relevant legal documentsbased on the factual patterns. In one embodiment, each legal document ofthe plurality of legal documents is associated with one or more judgesfrom a plurality of federal judges; wherein, when the instructions areexecuted with at least one processor, the following step is alsoexecuted: the optimization model assigns an ideological score each judgeof the plurality of federal judges; and wherein the optimization modelgenerates the recommended filing strategy using the ideological score ofthe judges associated with the relevant legal documents. In oneembodiment, when the instructions are executed with at least oneprocessor, the following step is also executed: the optimization modelpredicts an interpretation of the recommended filing strategy by eachjudge of the plurality of judges. In one embodiment, the interpretationof the recommended filing strategy by each judge of the plurality ofjudges comprises a first interpretation in favor of a government entityor a second interpretation in favor of a non-government entity. In oneembodiment, the interpretation of the recommended filing strategy byeach judge of the plurality of judges is based on either the strengthscore of the relevant legal documents or a judicial trend. In oneembodiment, wherein the user inputs are associated with a user; andwherein the risk tolerance classification indicates whether the user hasa high level of risk tolerance or a low level of risk tolerance. In oneembodiment, the combined media file is customized to the user and therisk tolerance of the user. In one embodiment, presenting, via thegraphical user interface, the combined media file comprises explainingthe recommended filing strategy to a user of the graphical userinterface. In one embodiment, wherein, when the instructions areexecuted with at least one processor, the following step is alsoexecuted: prepopulating templates using the recommended filing strategyand the user inputs.

It is understood that variations may be made in the foregoing withoutdeparting from the scope of the disclosure.

In several example embodiments, the elements and teachings of thevarious illustrative example embodiments may be combined in whole or inpart in some or all of the illustrative example embodiments. Inaddition, one or more of the elements and teachings of the variousillustrative example embodiments may be omitted, at least in part,and/or combined, at least in part, with one or more of the otherelements and teachings of the various illustrative embodiments.

Any spatial references such as, for example, “upper,” “lower,” “above,”“below,” “between,” “bottom,” “vertical,” “horizontal,” “angular,”“upwards,” “downwards,” “side-to-side,” “left-to-right,”“right-to-left,” “top-to-bottom,” “bottom-to-top,” “top,” “bottom,”“bottom-up,” “top-down,” etc., are for the purpose of illustration onlyand do not limit the specific orientation or location of the structuredescribed above.

In several example embodiments, while different steps, processes, andprocedures are described as appearing as distinct acts, one or more ofthe steps, one or more of the processes, and/or one or more of theprocedures may also be performed in different orders, simultaneously,and/or sequentially. In several example embodiments, the steps,processes and/or procedures may be merged into one or more steps,processes, and/or procedures.

In several example embodiments, one or more of the operational steps ineach embodiment may be omitted. Moreover, in some instances, somefeatures of the present disclosure may be employed without acorresponding use of the other features. Moreover, one or more of theabove-described embodiments and/or variations may be combined in wholeor in part with any one or more of the other above-described embodimentsand/or variations.

The phrase “at least one of A and B” should be understood to mean “A, B,or both A and B.” The phrase “one or more of the following: A, B, and C”should be understood to mean “A, B, C, A and B, B and C, A and C, or allthree of A, B, and C.” The phrase “one or more of A, B, and C” should beunderstood to mean “A, B, C, A and B, B and C, A and C, or all three ofA, B, and C.”

AI though several example embodiments have been described in detailabove, the embodiments described are examples only and are not limiting,and those skilled in the art will readily appreciate that many othermodifications, changes, and/or substitutions are possible in the exampleembodiments without materially departing from the novel teachings andadvantages of the present disclosure. Accordingly, all suchmodifications, changes, and/or substitutions are intended to be includedwithin the scope of this disclosure as defined in the following claims.In the claims, any means-plus-function clauses are intended to cover thestructures described herein as performing the recited function and notonly structural equivalents, but also equivalent structures. Moreover,it is the express intention of the applicant not to invoke 35 U.S.C. §112(f) for any limitations of any of the claims herein, except for thosein which the claim expressly uses the word “means” together with anassociated function.

What is claimed is:
 1. A method of generating and presenting arecommended tax filing strategy, the method comprising: receiving, usinga graphical user interface, user inputs including tax-relatedinformation about the user; identifying, using one or more computers,patterns of the user inputs for use in an optimization model; accessinglegal documents associated with a plurality of federal judges; assigningan ideological score to each judge of the plurality of federal judgesbased on 1) deference to taxpayers, 2) weight given to established caselaw or judicial trends and social impacts, or 3) both 1) and 2);generating, using the optimization model and based on the user inputtedtax-related information, the recommended tax filing strategy, whereinthe recommended tax filing strategy is generated using the ideologicalscores of the judges; predicting, using the optimization model, aninterpretation of the recommended tax filing strategy by each judge ofthe plurality of judges; identifying a plurality of media files, from alibrary of media files, based on the recommended tax filing strategy;creating a combined media file from the plurality of media files;presenting the combined media file to the user via the graphical userinterface; and prepopulating a first template using the recommended taxfiling strategy and/or the user inputs.
 2. The method of claim 1,further comprising: iteratively updating the ideological scores based onnewly entered judicial data.
 3. The method of claim 1, wherein theinterpretation of the recommended tax filing strategy by each judge ofthe plurality of federal judges comprises a first interpretation infavor of a government entity or a second interpretation in favor of anon-government entity.
 4. The method of claim 1, wherein theoptimization model assigns a strength score to each legal document; andwherein the interpretation of the recommended tax filing strategy byeach judge of the plurality of federal judges is based on either thestrength scores of the legal documents or a judicial trend of thejudicial trends.
 5. The method of claim 1, wherein presenting to theuser, via the graphical user interface, the combined media filecomprises explaining the recommended tax filing strategy to the user ofthe graphical user interface.
 6. The method of claim 1, furthercomprising: assigning, using the one or more computers and based on theidentified patterns, a risk tolerance classification; wherein therecommended tax filing strategy is generated using the risk toleranceclassification.
 7. The method of claim 6, wherein the risk toleranceclassification indicates whether the user has a high level of risktolerance or a low level of risk tolerance.
 8. The method of claim 7,wherein the combined media file is customized to the user and the risktolerance of the user.
 9. An apparatus configured to generate andpresent a recommended tax filing strategy, the apparatus comprising oneor more processors executing instructions comprising: receiving, using agraphical user interface, user inputs including tax-related informationabout the user; identifying patterns of the user inputs for use in anoptimization model; accessing legal documents associated with aplurality of federal judges; assigning an ideological score to eachjudge of the plurality of federal judges based on 1) deference totaxpayers, 2) weight given to established case law or judicial trendsand social impacts, or 3) both 1) and 2); generating, using theoptimization model and based on the user inputted tax-relatedinformation, the recommended tax filing strategy, wherein therecommended tax filing strategy is generated using the ideologicalscores of the judges; predicting, using the optimization model, aninterpretation of the recommended tax filing strategy by each judge ofthe plurality of judges; identifying a plurality of media files, from alibrary of media files, based on the recommended tax filing strategy;creating a combined media file from the plurality of media files;presenting the combined media file to the user via the graphical userinterface; and prepopulating a first template using the recommended taxfiling strategy and/or the user inputs.
 10. The apparatus of claim 9,wherein the instructions further comprise: iteratively updating theideological scores based on newly entered judicial data.
 11. Theapparatus of claim 9, wherein the interpretation of the recommended taxfiling strategy by each judge of the plurality of federal judgescomprises a first interpretation in favor of a government entity or asecond interpretation in favor of a non-government entity.
 12. Theapparatus of claim 9, wherein the optimization model assigns a strengthscore to each legal document; and wherein the interpretation of therecommended tax filing strategy by each judge of the plurality offederal judges is based on either the strength scores of the legaldocuments or a judicial trend of the judicial trends.
 13. The apparatusof claim 9, wherein presenting to the user, via the graphical userinterface, the combined media file comprises explaining the recommendedtax filing strategy to the user of the graphical user interface.
 14. Theapparatus of claim 9, wherein the instructions further comprise:assigning, based on the identified patterns, a risk toleranceclassification; wherein the recommended tax filing strategy is generatedusing the risk tolerance classification.
 15. The apparatus of claim 14,wherein the risk tolerance classification indicates whether the user hasa high level of risk tolerance or a low level of risk tolerance.
 16. Theapparatus of claim 15, wherein the combined media file is customized tothe user and the risk tolerance of the user.
 17. The method of claim 1,further comprising: prepopulating templates using the recommended taxfiling strategy and the user inputs, the templates comprising the firsttemplate.
 18. The apparatus of claim 9, wherein the instructions furthercomprise: prepopulating templates using the recommended tax filingstrategy and the user inputs, the templates comprising the firsttemplate.